Changes in microbial community structure and functioning with elevation are linked to local soil characteristics as well as climatic variables

Abstract Mountain forests are important carbon stocks and biodiversity hotspots but are threatened by increased insect outbreaks and climate‐driven forest conversion. Soil microorganisms play an eminent role in nutrient cycling in forest habitats and form the basis of soil food webs. Uncovering the driving factors shaping microbial communities and functioning at mountainsides across the world is of eminent importance to better understand their dynamics at local and global scales. We investigated microbial communities and their climatic and local soil‐related drivers along an elevational gradient (800–1700 m asl) of primary forests at Changbai Mountain, China. We analyzed substrate‐induced respiration and phospholipid fatty acids (PLFA) in litter and two soil layers at seven sites. Microbial biomass (Cmic) peaked in the litter layer and increased towards higher elevations. In the litter layer, the increase in Cmic and in stress indicator ratios was negatively correlated with Ca concentrations indicating increased nutritional stress in high microbial biomass communities at sites with lower Ca availability. PLFA profiles in the litter layer separated low and high elevations, but this was less pronounced in soil, suggesting that the litter layer functions as a buffer for soil microbial communities. Annual variations in temperature correlated with PLFA profiles in all three layers, while annual variations in precipitation correlated with PLFA profiles in upper soil only. Furthermore, the availability of resources, soil moisture, Ca concentrations, and pH structured the microbial communities. Pronounced changes in Cmic and stress indicator ratios in the litter layer between pine‐dominated (800–1100 m) and spruce‐dominated (1250–1700 m) forests indicated a shift in the structure and functioning of microbial communities between forest types along the elevational gradient. The study highlights strong changes in microbial community structure and functioning along elevational gradients, but also shows that these changes and their driving factors vary between soil layers. Besides annual variations in temperature and precipitation, carbon accumulation and nitrogen acquisition shape changes in microbial communities with elevation at Changbai Mountain.


| INTRODUC TI ON
Forests store large amounts of carbon, fixed in standing plant (tree) biomass and soil organic matter. Mountain forests contribute significantly to these carbon stocks as 41% of the worldwide mountain area is covered by forests and mountain forests sum up to 23% of the worldwide forest cover (Price et al., 2015). Global warming is expected to strongly alter mountain forests. Albrich et al. (2020) projected changes in coniferous mountain forests towards broadleaf forests at lower elevations in the European Alps. These changes in vegetation are likely to affect the structure and functioning of microbial and animal communities.
Although microbial communities along elevational gradients received more attention in the last years, there is still a lack of knowledge on the factors driving microbial community composition and functioning along such gradients (Looby & Martin, 2020). Studies addressing this lack of knowledge are best to be done in mountain areas little affected by humans allowing to uncover the response of natural communities to global change factors. The northern slope of Changbai Mountain in Northeast China represents such a natural forest gradient as these forests have never been logged (Tang et al., 2011). The forests comprise mainly primary forests with a transition between deciduous and mixed forests at lower elevations towards pure coniferous and birch forests at higher elevations (Liu, 1997;Tang et al., 2011).
Litter entering the belowground system is decomposed predominantly by microorganisms, mainly bacteria and fungi (Bani et al., 2018), and therefore, microorganisms play a critical role in the mineralization of carbon and nitrogen (Hobara et al., 2014). Considering that microbial activity is intricately linked to temperature, mountains provide ideal settings to investigate the role of temperature and associated changes in forest type on the structure and functioning of microbial communities. Studying these changes is of particular relevance in face of global climate change. With decreasing temperatures and shorter vegetation periods at higher elevation, microorganisms may have to concentrate their metabolic activities to the limited period of high temperature and microbial communities have to adapt to the short period they can be active. Conform to these assumptions, Massaccesi et al. (2020) found microbial biomass to increase with increasing elevation in coniferous forests in the European Apennine indicating higher resource availability at high elevations. Changbai Mountain forests at high elevations are dominated by spruce (Liu, 1997), and spruce is known to retard decomposition processes by a high concentration of polyphenols in needles contributing to the accumulation of carbon at high elevation (Gallet & Lebreton, 1995). This is likely to be associated with distinct microbial communities.
Harsh environmental conditions including climatic and soil factors at high elevations also likely increase the physiological stress of microorganisms. Both low temperature and pH are known to result in alterations in the structure of microbial membranes (Guckert et al., 1986;Knivett & Cullen, 1965;Russel, 2008), with major consequences for microbial community composition and functioning.
Conform to these considerations, Shen et al. (2013) identified pH as the main driver of changes in microbial community composition with elevation at Changbai Mountain. Effects of low temperature and pH on soil microorganisms, however, are likely to vary with soil depth due to the buffering of adverse climatic conditions by the litter layer and typically higher pH in litter than in soil. Further, the decreases in organic matter with soil depth and associated decline in resource availability (Hobley & Wilson, 2016;Kramer & Gleixner, 2008) may aggravate microbial stress in soil. Therefore, driving factors of microbial community structure and activity are likely to differ between litter and soil. As both processes in litter and soil contribute to carbon and nutrient cycling, understanding the driving factors of microbial community composition and functioning in both litter and soil is of fundamental importance. However, studies investigating changes in microbial communities along elevational gradients often only focus on soils and neglect the litter layer (Chang et al., 2016;Liu et al., 2019).
To investigate changes in microbial communities along environmental gradients phospholipid fatty acids (PLFAs) are commonly used (Chang et al., 2016;Liu et al., 2019;Xu et al., 2014). PLFAs form the major component of cell membranes and, by varying among microbial groups, provide insight into microbial community structure (Bossio & Scow, 1997;Frostegård et al., 2011;Moore-Kucera & Dick, 2008). Further, PLFA ratios serve as indicators of environmental stress and substrate availability (Bossio & Scow, 1997;Frostegård et al., 2011;Moore-Kucera & Dick, 2008). Thereby, PLFAs provide insight into changes in the structure and functioning of microbial communities along altitudinal gradients (Klimek et al., 2020;Liu et al., 2019). Similarly, microbial basal respiration and substrateinduced respiration (SIR) provide insight into gross characteristics of microbial communities such as microbial biomass and activity as well as the efficiency in the use of carbon resources by microorganisms (Anderson & Domsch, 1978, 1993Scheu, 1992).
We used PLFAs and SIR to follow changes in microbial community structure and functioning in litter and soil of forests along an altitudinal transect of Changbai Mountain, China. We hypothesized (i) microbial biomass and metabolic quotient to increase with increasing elevation but to decrease with soil depth; (ii) microbial community composition, represented by PLFA profiles, to change with elevation and soil depth, with the changes being less pronounced in soil than in litter; (iii) elevation-related climatic variables and pH to be the major factors structuring microbial communities in litter, while in soil local soil characteristics to be most important; and (iv) forest, microbes, mountain, nitrogen, organic carbon, PLFA

T A X O N O M Y C L A S S I F I C A T I O N
Microbial ecology physiological and nutritional stress indicators to increase with increasing elevation (due to increased environmental harshness) and soil depth (due to increased resource shortage).

| Study site and sampling
Changbai Mountain (42°8'25.4004"N, 128°7'36.2352″E) extends along the border between the Chinese provinces Jilin and Liaoning and North Korea, with the "Changbaishan" being the highest mountain (2750 m asl). Samples were taken along the northern slope of the mountain forming part of the "Changbaishan National Nature Reserve." The alkaline geological groups in the sampling area comprise stomatal and laminated basalt, alkali pumice, trachyte and tuff, reflecting the volcanic history of the mountain (Yan et al., 2018). The area belongs to the temperate climate regime and is characterized by long winters and short and warm summers. Between 1959 and 1988, the annual mean temperature ranged from −7 to 3°C and precipitation ranged from 700 to 1400 mm (Chen et al., 2011). The mountain vegetation mainly comprises broad-leaved and mixed forests with a high abundance of Korean pine (Pinus koraiensis Siebold & Zucc.) at lower elevation (up to 1100 m) and spruce-fir coniferous forests at higher elevation (up to 1700 m) followed by birch forests and tundra (Tang et al., 2011;Yu et al., 2013). The current study focuses on the forest area between 800 and 1700 m asl, where seven plots of an elevational difference of 150 m were sampled. Every plot was subdivided into four subplots with at least 50 m distance between them (Appendix Figure A1). Samples were taken in early September 2019.
Three soil cores of a diameter of 5.5 cm were randomly taken at each subplot, the cores were divided into litter layer, upper (0-5 cm) and lower (5-10 cm) soil layer. The three samples per layer were pooled and considered as one replicate, resulting in four replicates per elevation. Samples were transported in cooling boxes to the laboratory and frozen at −26°C. Prior to further analyses, thawed litter samples were cut into pieces of ca. 2.5 cm × 2.5 cm by scissors, and thawed soil samples were sieved through 2 mm mesh and thoroughly mixed.

| Chemical and microbial analyses
Soil and litter pH was measured in 0.01 M CaCl 2 solution. For carbon and nitrogen analyses 2 g of soil and 1 g of litter were dried at 70°C for 24 h and milled. Aliquots of ca. 1.5 mg of litter and ca. 10 mg of soil were transferred into tin capsules. Carbon and nitrogen content, and natural 13 C/ 12 C isotope ratios (Table 1) were measured using an isotopic mass spectrometer (Delta plus XP, Thermo Electron, Bremen, Germany) coupled via an interface (Conflo III, Thermo Electron, Bremen, Germany) to an elemental analyzer (Flash 2000, Thermo Fisher Scientific, Cambridge, UK).
The abundance of 13 C was expressed as δ values, calculated as , with R sample and R standard being the 13 C/ 12 C ratio in the sample and standard. Vienna Pee Dee belemnite was the primary standard for 13 C. Acetanilide was used as an internal standard.
A set of climatic variables retrieved from worldclim2 was ascribed to every elevational plot and extracted via the "raster" package at 30 s resolution (Fick & Hijmans, 2017;Hijmans, 2021 For measuring microbial respiration and biomass, samples were placed at 4°C for 72 h for thawing prior to the analyses and then preincubated for 7 days at room temperature. A total of 0.8 g of litter and 2 g of each soil layer were used for measuring basal respiration (BR) and substrate-induced respiration (SIR) following Anderson and Domsch (1978). O 2 consumption (μl O 2 g −1 soil dw h −1 ) was measured every 0.5 h at 22.0°C using an automated respirometer based on electrolytic O 2 compensation (Scheu, 1992). For BR, the mean of readings from 6 to 12 h after attachment of the vessels to the respirometer was used. For measuring SIR, a glucose solution was added with 80 mg g −1 dry weight added to litter and 8 mg g −1 dry weight to soil. The mean of the lowest three measurements of the glucoseamended samples was used as the maximum initial respiratory response (MIRR; μl O 2 g −1 dry weight h −1 ). Microbial biomass (C mic ) was calculated as MIRR ⨯ 38 ⨯ 0.7 (Beck et al., 1997). The specific respiration (qO 2 ; μl O 2 mg −1 C mic h −1 ) was calculated as a quotient between BR and C mic . To facilitate comparisons between soil layers C mic was expressed per gram organic carbon as mg C mic g −1 C.

| Statistical analyses
Statistical analyses were performed in R v 4.0.4 (R Core Team, 2021).
To analyze differences in microbial community composition among elevations and layers, Bray-Curtis distance-based PERMANOVAs were performed using the "adonis" function. The input matrix included amounts of PLFAs as mole percentages as dependent variables. Elevation, soil layer and their interaction were included as independent factors. Nonmetric multidimensional scaling (NMDS) was used to display differences in PLFA composition in 2-dimensional space. To identify the PLFAs responsible for most of the variation between elevations and soil layers, the Bray-Curtis distancebased analysis of similarity percentages ("SIMPER") was conducted (Oksanen et al., 2020).
To investigate environmental factors structuring the PLFA composition in litter and soil, redundancy analysis (RDA) was used. The response matrix was the same as for the Bray-Curtis distance-based method described above. While the response matrix was left unscaled, the matrix containing the environmental factors, including local soil factors (including the eleven elements) and climatic factors, was scaled to values between 0 and 1 to secure comparability of effects. RDAs were calculated for all three layers and predictors were selected after correlation and co-linearity between each other; pH was included in all RDA models since it has been identified as the main structuring force for microbial communities at Changbai Mountain (Shen et al., 2013). With this preselected set of explanatory variables, a permutational, p-value-based forward selection was run via the "ordistep" function (Oksanen et al., 2020). The number of permutations was 1000. The significance of the variation explained by the selected model and its predictors was tested with the permutational-based "anova.cca" function and their explanatory impact was analyzed via the adjusted R 2 -values of the model (Oksanen et al., 2020). The RDA model was displayed as 2-dimensional biplot of "species"-scaled values to focus on the impact of the factors characterizing community composition.
Variations in C mic and qO 2 with elevation and soil layer were inspected using linear mixed-effects models with plot-ID as a random term (Bates et al., 2022); if necessary, data were log 10 transformed to approximate Gaussian distribution. Independent variables were elevation, soil layer and their interaction. If the interaction between elevation and soil layer was significant each layer was analyzed separately, using multiple linear models with the respective dependent variable as mentioned above and elevation as an independent factor. Linear models met the assumption of homoscedasticity and independence. The independent factor elevation was ordered in all analyses. For visualization of pairwise differences in figures, we computed Tukey's honestly significant difference (HSD) using the "emmeans" package (Lenth, 2022). Errors presented in text and figures represent the standard error of the mean (SEM). To gain a better understanding of the observed changes, we correlated factors varying with elevation (C mic , qO 2 , cyclo/pre and mono/sat ratios) with the environmental factors, which were identified by forward selection in the RDAs to significantly affect the PLFA patterns (δ 13 C, C/N, pH, Ca concentration, water content) using "Spearman rank correlation" to account for nonlinear relationships revealed by visual inspection.

| Microbial biomass across elevations and layers
To study the expected variations in microbial biomass (C mic ), we tested the influence of elevation and layer on C mic and their interaction. Microbial biomass varied strongly among layers and generally declined from the litter layer (42.08 ± 1.84 mg C mic g −1 C) to 0-5 and 5-10 cm soil by 75% and 73%, respectively, but the decline varied with elevation (significant layer ⨯ elevation interaction; χ 2 = 24.65, p = .017). A separate analysis of each layer showed that C mic only varied significantly with elevation in litter (F 6,21 = 2.67, p = .044), where it first declined from 800 (38.82 ± 3.58 mg C mic g −1 C) to 1100 m by 18% and then increased from 1100 m (31.83 ± 3.93 mg C mic g −1 C) up to 1700 m by 61% (Figure 1). By contrast, in 0-5 and 5-10 cm soil C mic did not show a clear pattern, but was generally low at 1100 m and high at 1250 m. In contrast to C mic , qO 2 varied significantly with elevation (χ 2 = 13.95, p = .03) but not among soil layers; it was generally low at 950 m (overall mean across layers 5.49 ± 0.33 μl O 2 mg −1 C mic h −1 ) and highest at 1700 m (6.41 ± 0.30 μl O 2 mg −1 C mic h −1 ), but the variations were generally small (Appendix Figure A2).

| Microbial community composition across elevations and layers
Due to the significant interaction between layer and elevation, we inspected the layers separately and displayed the PLFA profiles of individual layers (Figure 2). In the litter layer PLFA profiles sig-  Table A2). In 0-5 cm depth, the PLFA pattern generally resembled that in litter, however, the PLFA accounting for most of the dissimilarity between 800 and 1700 m was 18:1ω7 (2.41%; Appendix Table A2). In 5-10 cm depth, 800 m separated from the higher elevations, being most dissimilar to 1700 m (group dissimilarity 10.56%), with PLFA a15:0 accounting for most of the dissimilarity (2.34%, Appendix Table A2). Branchedchain PLFAs a15:0, i16:0 and cy17:0 were associated with 800, 950 and 1100 m, while the unsaturated PLFAs 18:2ω6,9 and 18:1ω7 were most abundant at 1400, 1550 and 1700 m.
As indicated by RDA, the environmental factors that correlated with certain PLFAs varied between layers (Table 2, Figure 3) and F I G U R E 1 Changes in microbial biomass with elevation in litter, 0-5 and 5-10 cm soil depth. The solid line represents the mean across elevations, the dots represent data points, error bars represent the standard error of the mean and letters mark significant differences between means (Tukey's HSD test at p < .05). For results of linear models, see text.

| Indicators of community changes and nutritional stress
Of the four common PLFA indicator ratios, the fun/bac PLFA ratio significantly decreased from litter (overall mean 0.8 ± 0.18) to 0-5 and 5-10 cm depth by 89.2% and 91.4%, respectively (χ 2 = 278.58, p < .001; Figure 4a); it did not vary significantly with elevation. The cyclo/pre ratio, as a measure of physiological stress, significantly decreased from litter (overall mean 0.15 ± 0.01) to 0-5 and 5-10 cm by 14.9% and 5.7%, respectively (χ 2 = 10.25, p = .006; Figure 4b); however, the decline depended on elevation (significant elevation ⨯ layer interaction; χ 2 = 40.96, p < .001). As indicated by separately   Precipitation seasonality --5.00 .010 -Note: Environmental factors were chosen via p-value based forward selection per layer. All selected factors are displayed; "-" indicates that factors were not chosen for the respective layer. pH was included in all RDAs due to its importance for microbial community composition shown in a previous study at Changbai Mountain (Shen et al., 2013).

TA B L E 2 F-and p-values for pH, Ca
concentrations, C/N ratio, δ 13 C values, water content, temperature seasonality and precipitation seasonality as predictors of PLFA patterns in litter, 0-5 and 5-10 cm soil as analyzed by RDA and presented in Figure 3. Supporting our first hypothesis, C mic strongly decreased from litter to 0-5 and 5-10 cm soil depth, presumably reflecting the decrease in resource availability from litter to deeper soil layers. However, qO 2 did not differ significantly between soil layers suggesting that the efficiency in the use of carbon resources by microorganisms is similar across soil layers (Cao et al., 2019). Interestingly, C mic responded differently to the elevational gradient in litter and soil. In litter, C mic increased with increasing elevation above 1100 m and correlated negatively with the concentration of Ca along the elevational gradient.  (Castanier et al., 1999;Krajewska, 2018). The role of Ca and the contribution of microorganisms to the cycling of nitrogen has been investigated in detail in arable soils (Bowles et al., 2014;Klose & Tabatabai, 2000), while its role in forest soils remains little studied. Klose and Tabatabai (1999) found urease activity to be mainly of microbial origin in a variety of soils, underlining the potential influence of Ca on the mobilization of nitrogen and microbial nitrogen nutrition.
The increases in C mic and in part of qO 2 towards higher elevations, and its (strongly) negative correlation with Ca (and pH) and (moderately) positive correlation with litter C/N ratio may reflect that nutritional shortage is more pronounced in communities of high C mic and microbial activity. In fact, microbial activity can increase with stronger nitrogen limitation and decrease with the addition of nitrogen (Averill & Waring, 2018;Craine et al., 2007) following the "microbial nitrogen mining" hypothesis (Moorhead & Sinsabaugh, 2006). Wild et al. (2017) showed that a short-term input of carbon increases microbial growth and the microbial demand for nitrogen, but does not influence nitrogen mining. Therefore, high carbon availability at high elevations may also explain the positive correlation between PLFA stress indicators and litter C/N ratio due to increased nitrogen demand and increased C mic . In addition, high Ca concentrations at lower elevations may facilitate microbial nitrogen acquisition and therefore result in lower microbial stress. Overall, our first hypothesis was only supported in part; in the litter layer, C mic responded as hypothesized, even though not linear, with the main drivers being variations in the availability of carbon and nitrogen but also Ca along the elevational gradient, while C mic in the two soil layers was rather constant across elevations.
Supporting our second hypothesis, PLFA profiles clearly separated the three layers, and this was mainly due to the decrease in fungal PLFA markers from the litter to the two soil layers and the decrease in Gram − bacterial markers from 0-5 to 5-10 cm. This is in line with the results of the study by Šnajdr et al. (2008), who documented a rapid decrease in fungal biomass from the litter to the fermentation layer in forests. Fungi are known to be the major decomposers of recalcitrant carbon compounds and typically dominate in the litter layer, while bacteria play a larger role in the decomposition of root exudates thereby dominating in soil (de Boer et al., 2005). Further, the Gram + /Gram − ratio increased with soil depth, since Gram − bacteria heavily depend on plant-derived carbon, such as litter, while Gram + bacteria preferentially use soil organic matter-derived carbon (Kramer & Gleixner, 2008).
PLFA profiles in the litter layer also varied with elevation, and temperature seasonality was the only environmental variable studied significantly affecting them, which is in line with our third hypothesis, even though we expected more climatic variables to influence PLFA profiles in litter. Temperature seasonality represents the variation in temperature during the year and litter is more heavily exposed to such fluctuations in temperature than deeper soil layers.
Generally, increasing temperature accelerates the decomposition of litter (Kirschbaum, 1995) resulting in more shallow organic layers (Raich et al., 2006). Associated with higher temperatures, the decomposition rates of forest litter typically increase towards lower elevations (Salinas et al., 2011). However, in addition to the increase in temperature at lower elevations, temperature variation within the year also increases at lower elevations, and the vegetative period starts earlier and lasts longer compared with higher elevations.
In spring decomposition rates of litter strongly increase (Kreyling et al., 2013), but at higher elevations this is less pronounced resulting in litter accumulation and reduced nutrient mobilization.
Although litter decomposition is hampered during winter it does not stop and may benefit from snow cover preventing or reducing the freezing of litter and soil (Kreyling et al., 2013;Schimel et al., 2004Schimel et al., , 2007. Uchida et al. (2005) reported that 26% of the annual mass loss of litter occurs under snow. Notably, the interception of snow by trees is higher, and therefore, snow cover is sparser in evergreen coniferous compared with deciduous forests (Noguchi & Nishizono, 2010;Vikhamar & Solberg, 2003). This reduced snow cover, which is related to low-temperature seasonality, together with low-quality needle litter may explain the accumulation of litter at high elevations, while the opposite may be true at low elevations, with these differences likely affecting microbial biomass and com- F I G U R E 4 Changes in the (a) fungal/bacterial (fun/bac), (b) cyclopropyl/monoenoic (cyclo/pre), (c) saturated/monounsaturated (sat/mono) and (d) Gram + /Gram − marker PLFA ratios (Gram + /Gram − ) in litter, 0-5 and 5-10 cm soil depth with elevation. The solid line represents the overall mean, the dots the data points. Error bars represent the standard error of the mean and letters mark significant differences between means (Tukey's HSD test at p < .05). For results of linear models see text.
Notably, the C/N ratio in 0-5 cm depth was much lower than in the litter layer indicating increased microbial access to nitrogen. Across the elevational gradient, the C/N ratio in 0-5 cm depth was highest at 1250 m and this was associated with an increase in PLFA 15:0 and an increased sat/mono ratio pointing to nutritional stress at this nitrogen-poor site. Additionally, C mic was high at 1250 m and, as in the litter layer, this may have aggravated nitrogen limitation (Dubinkina et al., 2019). Another soil-related factor that correlated with microbial community structure in 0-5 cm depth was δ 13 C values of soil organic matter. δ 13 C increased towards higher elevations indicating an increasing state of decomposition of organic matter (Melillo et al., 1989;Potapov et al., 2019), related to high microbial biomass and activity in litter. Other soil factors driving the PLFA composition in 0-5 cm depth were Ca concentrations and pH, which increased towards lower elevations, indicating again that the effect of pH on microbial community composition at our study sites is not linked to physiological stress by acidity but the abundance of base cations. Variations in Ca concentrations rather than pH itself may be responsible for the widely reported correlation between pH and the structure of microbial communities (Högberg et al., 2007;Männistö et al., 2007;Zhou et al., 2017).
Besides these local soil-related factors, temperature seasonality explained a large fraction of the variation in PLFA profiles in 0-5 and 5-10 cm depth, and in 0-5 cm also precipitation seasonality, contrasting the litter layer. Changbai Mountain has a rather constant warm climate during the relatively short vegetative period followed by harsh winters with mean monthly temperatures below −20°C in January (Yu et al., 2013). Temperature and precipitation seasonality increase towards lower elevations, reflecting longer and warmer summers as well as more pronounced seasonality at lower elevations. In particular marker PLFAs for Gram + bacteria increased towards lower elevations, especially in 5-10 cm depth, where the Gram + /Gram − ratio was highest at 800 m. Due to their strong and interlinked peptidoglycan cell walls, Gram + bacteria are more resistant to temperature and moisture changes than Gram − bacteria (Schimel et al., 2007). Interestingly, the Gram + /Gram − decreased from 800 to 1100 m and this was most pronounced in 5-10 cm depth. Gram − bacteria depend more heavily on labile carbon resources, while Gram + bacteria can access more recalcitrant carbon compounds (Fanin et al., 2019;Kramer & Gleixner, 2008). High microbial activity and biomass due to high temperatures during the vegetative period may hamper the leaching of labile carbon compounds into the soil, which is supported by the strong increase in the Gram + /Gram − ratio from litter to 0-5 and 5-10 cm soil depth. Notably, we took our samples in September before the deciduous trees shed their leaves, and the litter layer comprised predominantly leaf litter material of the previous year depleted in labile compounds, which may have contributed to the low availability of labile carbon compounds in soil and therefore to the increase in Gram + bacteria in soil at 800 m.
The identified effects of temperature seasonality on the structure and functioning of microbial community in each of the layers are of special relevance for the response of decomposer systems and decomposition processes to global warming, which is expected to be associated with increased seasonal temperature fluctuations (Tian et al., 2015). Transplantation experiments along elevational gradients showed decomposition to increase in litter translocated to lower elevations (Salinas et al., 2011), where temperature and temperature seasonality are higher. Therefore, climate change may affect in particular the functioning of microbial communities at high elevations with potential detrimental consequences for carbon sequestration.
Contrasting our fourth hypothesis both stress indicator ratios were highest in the litter layer, but their response also depended on

| CON CLUS ION
Our study aimed at uncovering variations in microbial community composition and functioning along a natural elevational gradient of forests and identifying the factors responsible for these variations. We identified temperature and precipitation seasonality as major climatic factors driving microbial communities in litter and soil, which is likely due to the pronounced difference between harsh winters, and constant warm and wet summers at Changbai Mountain. funding acquisition (lead); project administration (lead); resources (equal); supervision (lead); writing -review and editing (lead).

ACK N OWLED G M ENTS
This work was supported by the National Natural Science Foundation of China (No. 31861133006, 42071059) and the DFG (SCHE/376/42-1) in the framework of the Sino-German collaboration.
We thank Theodora Volovei and Guido Humpert for their help during laboratory work, Liang Chang for his help in communication and sampling during fieldwork, and Garvin Schulz for his advice for the redundancy analysis. We appreciate the support by the Open-Access-Publication-Found of the Göttingen State and University Library.
Open access funding enabled and organized by Projekt DEAL.

FU N D I N G I N FO R M ATI O N
Open access funding enabled and organized by project DEAL.

CO N FLI C T O F I NTE R E S T
The authors declare no conflict of interest.  (Erhardt et al., 2022).